A major effort in empirical asset pricing research is the initial stage of gathering the data, cleaning and filtering it, and then formatting it in a way that simplifies further statistical analysis. This process, when done properly, takes a large portion of a researcher’s time when it would be better spent on doing the actual analysis. By developing a package that automates much of the data import, cleaning, filtering and standardization process, a substantial fraction of the researcher’s time will be saved, while automating a significant portion of the data gathering and management aspect of asset pricing research. We expect this last aspect to support the reproducibility of research by academics and financial professionals. Our over-arching goal is to make the EAPR package an ideal support tool for the wide range of asset pricing research as described in Ball, Engle, and Murray (2016), and for quantitative portfolio construction research. The initial version of the package will work very effectively with asset prices, returns and factors (exposures) data delivered by Wharton Research Data Services, a major source of empirical data for academic asset pricing researchers.